Overview

Dataset statistics

Number of variables47
Number of observations850
Missing cells8831
Missing cells (%)22.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory335.5 KiB
Average record size in memory404.2 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric6
Boolean2

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-17959/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (89.1%)Imbalance
위생업태명 is highly imbalanced (78.3%)Imbalance
사용끝지하층 is highly imbalanced (63.9%)Imbalance
건물소유구분명 is highly imbalanced (79.0%)Imbalance
세탁기수 is highly imbalanced (54.0%)Imbalance
여성종사자수 is highly imbalanced (76.9%)Imbalance
남성종사자수 is highly imbalanced (76.9%)Imbalance
인허가취소일자 has 850 (100.0%) missing valuesMissing
폐업일자 has 149 (17.5%) missing valuesMissing
휴업시작일자 has 850 (100.0%) missing valuesMissing
휴업종료일자 has 850 (100.0%) missing valuesMissing
재개업일자 has 850 (100.0%) missing valuesMissing
전화번호 has 81 (9.5%) missing valuesMissing
도로명주소 has 494 (58.1%) missing valuesMissing
도로명우편번호 has 509 (59.9%) missing valuesMissing
좌표정보(X) has 110 (12.9%) missing valuesMissing
좌표정보(Y) has 110 (12.9%) missing valuesMissing
건물지상층수 has 174 (20.5%) missing valuesMissing
사용끝지상층 has 447 (52.6%) missing valuesMissing
발한실여부 has 60 (7.1%) missing valuesMissing
조건부허가신고사유 has 850 (100.0%) missing valuesMissing
조건부허가시작일자 has 850 (100.0%) missing valuesMissing
조건부허가종료일자 has 850 (100.0%) missing valuesMissing
회수건조수 has 691 (81.3%) missing valuesMissing
다중이용업소여부 has 56 (6.6%) missing valuesMissing
사용끝지상층 is highly skewed (γ1 = 20.03831128)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 301 (35.4%) zerosZeros
사용끝지상층 has 23 (2.7%) zerosZeros
회수건조수 has 30 (3.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:18:03.704072
Analysis finished2024-05-11 06:18:05.316044
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
3070000
850 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 850
100.0%

Length

2024-05-11T15:18:05.445828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:05.636574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 850
100.0%

관리번호
Text

UNIQUE 

Distinct850
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-05-11T15:18:05.981488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters18700
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique850 ?
Unique (%)100.0%

Sample

1st row3070000-205-1987-02306
2nd row3070000-205-1987-02308
3rd row3070000-205-1987-02310
4th row3070000-205-1987-02312
5th row3070000-205-1987-02313
ValueCountFrequency (%)
3070000-205-1987-02306 1
 
0.1%
3070000-205-2004-00003 1
 
0.1%
3070000-205-2002-00008 1
 
0.1%
3070000-205-2002-00019 1
 
0.1%
3070000-205-2002-00009 1
 
0.1%
3070000-205-2002-00010 1
 
0.1%
3070000-205-2002-00011 1
 
0.1%
3070000-205-2002-00012 1
 
0.1%
3070000-205-2002-00013 1
 
0.1%
3070000-205-2002-00014 1
 
0.1%
Other values (840) 840
98.8%
2024-05-11T15:18:07.028124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7385
39.5%
- 2550
 
13.6%
2 1996
 
10.7%
7 1351
 
7.2%
3 1206
 
6.4%
5 1178
 
6.3%
9 980
 
5.2%
1 879
 
4.7%
8 568
 
3.0%
4 309
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16150
86.4%
Dash Punctuation 2550
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7385
45.7%
2 1996
 
12.4%
7 1351
 
8.4%
3 1206
 
7.5%
5 1178
 
7.3%
9 980
 
6.1%
1 879
 
5.4%
8 568
 
3.5%
4 309
 
1.9%
6 298
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 2550
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7385
39.5%
- 2550
 
13.6%
2 1996
 
10.7%
7 1351
 
7.2%
3 1206
 
6.4%
5 1178
 
6.3%
9 980
 
5.2%
1 879
 
4.7%
8 568
 
3.0%
4 309
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7385
39.5%
- 2550
 
13.6%
2 1996
 
10.7%
7 1351
 
7.2%
3 1206
 
6.4%
5 1178
 
6.3%
9 980
 
5.2%
1 879
 
4.7%
8 568
 
3.0%
4 309
 
1.7%
Distinct540
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
Minimum1987-01-17 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T15:18:07.283534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:07.597224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
3
701 
1
149 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 701
82.5%
1 149
 
17.5%

Length

2024-05-11T15:18:07.873092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:08.120046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 701
82.5%
1 149
 
17.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
폐업
701 
영업/정상
149 

Length

Max length5
Median length2
Mean length2.5258824
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 701
82.5%
영업/정상 149
 
17.5%

Length

2024-05-11T15:18:08.364501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:08.655536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 701
82.5%
영업/정상 149
 
17.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2
701 
1
149 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 701
82.5%
1 149
 
17.5%

Length

2024-05-11T15:18:08.861802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:09.059498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 701
82.5%
1 149
 
17.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
폐업
701 
영업
149 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row영업

Common Values

ValueCountFrequency (%)
폐업 701
82.5%
영업 149
 
17.5%

Length

2024-05-11T15:18:09.325209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:09.583373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 701
82.5%
영업 149
 
17.5%

폐업일자
Date

MISSING 

Distinct553
Distinct (%)78.9%
Missing149
Missing (%)17.5%
Memory size6.8 KiB
Minimum1989-01-12 00:00:00
Maximum2024-03-04 00:00:00
2024-05-11T15:18:09.851781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:10.137632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB

전화번호
Text

MISSING 

Distinct682
Distinct (%)88.7%
Missing81
Missing (%)9.5%
Memory size6.8 KiB
2024-05-11T15:18:10.644367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.06502
Min length6

Characters and Unicode

Total characters7740
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique641 ?
Unique (%)83.4%

Sample

1st row0209268025
2nd row0209164073
3rd row0209263923
4th row0209263973
5th row0209241030
ValueCountFrequency (%)
02 464
35.7%
0200000000 19
 
1.5%
0 17
 
1.3%
00000 16
 
1.2%
913 6
 
0.5%
941 6
 
0.5%
927 4
 
0.3%
909 4
 
0.3%
922 4
 
0.3%
924 3
 
0.2%
Other values (706) 755
58.2%
2024-05-11T15:18:11.484243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1649
21.3%
2 1338
17.3%
9 1020
13.2%
663
8.6%
1 607
 
7.8%
6 448
 
5.8%
4 428
 
5.5%
3 412
 
5.3%
7 406
 
5.2%
8 398
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7077
91.4%
Space Separator 663
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1649
23.3%
2 1338
18.9%
9 1020
14.4%
1 607
 
8.6%
6 448
 
6.3%
4 428
 
6.0%
3 412
 
5.8%
7 406
 
5.7%
8 398
 
5.6%
5 371
 
5.2%
Space Separator
ValueCountFrequency (%)
663
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7740
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1649
21.3%
2 1338
17.3%
9 1020
13.2%
663
8.6%
1 607
 
7.8%
6 448
 
5.8%
4 428
 
5.5%
3 412
 
5.3%
7 406
 
5.2%
8 398
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1649
21.3%
2 1338
17.3%
9 1020
13.2%
663
8.6%
1 607
 
7.8%
6 448
 
5.8%
4 428
 
5.5%
3 412
 
5.3%
7 406
 
5.2%
8 398
 
5.1%
Distinct453
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-05-11T15:18:12.215154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9823529
Min length3

Characters and Unicode

Total characters4235
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)43.9%

Sample

1st row27.60
2nd row10.18
3rd row32.46
4th row56.00
5th row26.40
ValueCountFrequency (%)
33.00 37
 
4.4%
19.80 33
 
3.9%
00 32
 
3.8%
23.10 31
 
3.6%
16.50 30
 
3.5%
26.40 23
 
2.7%
24.00 20
 
2.4%
22.00 16
 
1.9%
18.00 13
 
1.5%
21.00 11
 
1.3%
Other values (443) 604
71.1%
2024-05-11T15:18:13.354640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 897
21.2%
. 850
20.1%
2 491
11.6%
1 451
10.6%
3 302
 
7.1%
4 262
 
6.2%
6 236
 
5.6%
5 225
 
5.3%
9 210
 
5.0%
8 190
 
4.5%
Other values (2) 121
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3383
79.9%
Other Punctuation 852
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 897
26.5%
2 491
14.5%
1 451
13.3%
3 302
 
8.9%
4 262
 
7.7%
6 236
 
7.0%
5 225
 
6.7%
9 210
 
6.2%
8 190
 
5.6%
7 119
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 850
99.8%
, 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 897
21.2%
. 850
20.1%
2 491
11.6%
1 451
10.6%
3 302
 
7.1%
4 262
 
6.2%
6 236
 
5.6%
5 225
 
5.3%
9 210
 
5.0%
8 190
 
4.5%
Other values (2) 121
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 897
21.2%
. 850
20.1%
2 491
11.6%
1 451
10.6%
3 302
 
7.1%
4 262
 
6.2%
6 236
 
5.6%
5 225
 
5.3%
9 210
 
5.0%
8 190
 
4.5%
Other values (2) 121
 
2.9%
Distinct148
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-05-11T15:18:13.944302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0411765
Min length6

Characters and Unicode

Total characters5135
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)4.5%

Sample

1st row136055
2nd row136865
3rd row136053
4th row136054
5th row136052
ValueCountFrequency (%)
136060 21
 
2.5%
136841 21
 
2.5%
136833 19
 
2.2%
136110 19
 
2.2%
136800 19
 
2.2%
136815 18
 
2.1%
136865 17
 
2.0%
136858 17
 
2.0%
136826 16
 
1.9%
136042 16
 
1.9%
Other values (138) 667
78.5%
2024-05-11T15:18:14.730387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1128
22.0%
3 1078
21.0%
6 1008
19.6%
8 652
12.7%
0 451
 
8.8%
4 213
 
4.1%
5 191
 
3.7%
7 171
 
3.3%
2 151
 
2.9%
9 57
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5100
99.3%
Dash Punctuation 35
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1128
22.1%
3 1078
21.1%
6 1008
19.8%
8 652
12.8%
0 451
 
8.8%
4 213
 
4.2%
5 191
 
3.7%
7 171
 
3.4%
2 151
 
3.0%
9 57
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1128
22.0%
3 1078
21.0%
6 1008
19.6%
8 652
12.7%
0 451
 
8.8%
4 213
 
4.1%
5 191
 
3.7%
7 171
 
3.3%
2 151
 
2.9%
9 57
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1128
22.0%
3 1078
21.0%
6 1008
19.6%
8 652
12.7%
0 451
 
8.8%
4 213
 
4.1%
5 191
 
3.7%
7 171
 
3.3%
2 151
 
2.9%
9 57
 
1.1%
Distinct779
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-05-11T15:18:15.175188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length25.208235
Min length18

Characters and Unicode

Total characters21427
Distinct characters152
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique713 ?
Unique (%)83.9%

Sample

1st row서울특별시 성북구 동선동5가 17-0번지
2nd row서울특별시 성북구 하월곡동 59-12번지
3rd row서울특별시 성북구 동선동3가 259-7번지
4th row서울특별시 성북구 동선동4가 90-1번지
5th row서울특별시 성북구 동선동2가 142-0번지
ValueCountFrequency (%)
서울특별시 850
22.3%
성북구 850
22.3%
장위동 138
 
3.6%
정릉동 130
 
3.4%
하월곡동 85
 
2.2%
길음동 83
 
2.2%
석관동 82
 
2.1%
종암동 73
 
1.9%
돈암동 48
 
1.3%
상가동 41
 
1.1%
Other values (948) 1436
37.6%
2024-05-11T15:18:15.995748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3674
 
17.1%
1015
 
4.7%
1 912
 
4.3%
886
 
4.1%
871
 
4.1%
852
 
4.0%
850
 
4.0%
850
 
4.0%
850
 
4.0%
850
 
4.0%
Other values (142) 9817
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12536
58.5%
Decimal Number 4354
 
20.3%
Space Separator 3674
 
17.1%
Dash Punctuation 751
 
3.5%
Open Punctuation 41
 
0.2%
Close Punctuation 41
 
0.2%
Uppercase Letter 15
 
0.1%
Lowercase Letter 10
 
< 0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1015
 
8.1%
886
 
7.1%
871
 
6.9%
852
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
796
 
6.3%
Other values (116) 3866
30.8%
Decimal Number
ValueCountFrequency (%)
1 912
20.9%
2 683
15.7%
3 498
11.4%
0 469
10.8%
5 341
 
7.8%
6 325
 
7.5%
4 315
 
7.2%
8 298
 
6.8%
7 282
 
6.5%
9 231
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 5
33.3%
A 4
26.7%
K 2
 
13.3%
S 2
 
13.3%
T 1
 
6.7%
P 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
s 3
30.0%
e 3
30.0%
k 3
30.0%
b 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
@ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
3674
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 751
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12536
58.5%
Common 8866
41.4%
Latin 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1015
 
8.1%
886
 
7.1%
871
 
6.9%
852
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
796
 
6.3%
Other values (116) 3866
30.8%
Common
ValueCountFrequency (%)
3674
41.4%
1 912
 
10.3%
- 751
 
8.5%
2 683
 
7.7%
3 498
 
5.6%
0 469
 
5.3%
5 341
 
3.8%
6 325
 
3.7%
4 315
 
3.6%
8 298
 
3.4%
Other values (6) 600
 
6.8%
Latin
ValueCountFrequency (%)
B 5
20.0%
A 4
16.0%
s 3
12.0%
e 3
12.0%
k 3
12.0%
K 2
 
8.0%
S 2
 
8.0%
T 1
 
4.0%
P 1
 
4.0%
b 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12536
58.5%
ASCII 8891
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3674
41.3%
1 912
 
10.3%
- 751
 
8.4%
2 683
 
7.7%
3 498
 
5.6%
0 469
 
5.3%
5 341
 
3.8%
6 325
 
3.7%
4 315
 
3.5%
8 298
 
3.4%
Other values (16) 625
 
7.0%
Hangul
ValueCountFrequency (%)
1015
 
8.1%
886
 
7.1%
871
 
6.9%
852
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
850
 
6.8%
796
 
6.3%
Other values (116) 3866
30.8%

도로명주소
Text

MISSING 

Distinct348
Distinct (%)97.8%
Missing494
Missing (%)58.1%
Memory size6.8 KiB
2024-05-11T15:18:16.586206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length30.75
Min length21

Characters and Unicode

Total characters10947
Distinct characters165
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique340 ?
Unique (%)95.5%

Sample

1st row서울특별시 성북구 보문로30길 72 (동선동2가)
2nd row서울특별시 성북구 삼선교로4길 10 (삼선동1가)
3rd row서울특별시 성북구 고려대로11길 6 (안암동2가)
4th row서울특별시 성북구 보국문로 157 (정릉동)
5th row서울특별시 성북구 개운사길 60 (안암동5가)
ValueCountFrequency (%)
서울특별시 356
 
17.4%
성북구 356
 
17.4%
장위동 55
 
2.7%
정릉동 49
 
2.4%
1층 39
 
1.9%
석관동 31
 
1.5%
하월곡동 30
 
1.5%
상가동 29
 
1.4%
종암동 24
 
1.2%
길음동 18
 
0.9%
Other values (556) 1063
51.9%
2024-05-11T15:18:17.393627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1694
 
15.5%
474
 
4.3%
1 414
 
3.8%
395
 
3.6%
394
 
3.6%
( 372
 
3.4%
) 372
 
3.4%
363
 
3.3%
356
 
3.3%
356
 
3.3%
Other values (155) 5757
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6500
59.4%
Decimal Number 1740
 
15.9%
Space Separator 1694
 
15.5%
Open Punctuation 372
 
3.4%
Close Punctuation 372
 
3.4%
Other Punctuation 204
 
1.9%
Dash Punctuation 48
 
0.4%
Uppercase Letter 8
 
0.1%
Lowercase Letter 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
474
 
7.3%
395
 
6.1%
394
 
6.1%
363
 
5.6%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
Other values (130) 2738
42.1%
Decimal Number
ValueCountFrequency (%)
1 414
23.8%
2 301
17.3%
3 187
10.7%
4 177
10.2%
0 163
 
9.4%
5 143
 
8.2%
8 101
 
5.8%
6 100
 
5.7%
7 83
 
4.8%
9 71
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
37.5%
A 3
37.5%
K 1
 
12.5%
S 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
s 3
37.5%
k 3
37.5%
e 1
 
12.5%
b 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 203
99.5%
@ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1694
100.0%
Open Punctuation
ValueCountFrequency (%)
( 372
100.0%
Close Punctuation
ValueCountFrequency (%)
) 372
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6500
59.4%
Common 4431
40.5%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
474
 
7.3%
395
 
6.1%
394
 
6.1%
363
 
5.6%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
Other values (130) 2738
42.1%
Common
ValueCountFrequency (%)
1694
38.2%
1 414
 
9.3%
( 372
 
8.4%
) 372
 
8.4%
2 301
 
6.8%
, 203
 
4.6%
3 187
 
4.2%
4 177
 
4.0%
0 163
 
3.7%
5 143
 
3.2%
Other values (7) 405
 
9.1%
Latin
ValueCountFrequency (%)
B 3
18.8%
A 3
18.8%
s 3
18.8%
k 3
18.8%
e 1
 
6.2%
b 1
 
6.2%
K 1
 
6.2%
S 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6500
59.4%
ASCII 4447
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1694
38.1%
1 414
 
9.3%
( 372
 
8.4%
) 372
 
8.4%
2 301
 
6.8%
, 203
 
4.6%
3 187
 
4.2%
4 177
 
4.0%
0 163
 
3.7%
5 143
 
3.2%
Other values (15) 421
 
9.5%
Hangul
ValueCountFrequency (%)
474
 
7.3%
395
 
6.1%
394
 
6.1%
363
 
5.6%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
356
 
5.5%
Other values (130) 2738
42.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct132
Distinct (%)38.7%
Missing509
Missing (%)59.9%
Infinite0
Infinite (%)0.0%
Mean2786.0909
Minimum2701
Maximum2880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-05-11T15:18:17.645368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2701
5-th percentile2710
Q12743
median2787
Q32827
95-th percentile2867
Maximum2880
Range179
Interquartile range (IQR)84

Descriptive statistics

Standard deviation49.324978
Coefficient of variation (CV)0.017704009
Kurtosis-1.0792776
Mean2786.0909
Median Absolute Deviation (MAD)42
Skewness0.070112052
Sum950057
Variance2432.9535
MonotonicityNot monotonic
2024-05-11T15:18:17.977906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2831 10
 
1.2%
2709 6
 
0.7%
2754 6
 
0.7%
2717 6
 
0.7%
2829 6
 
0.7%
2737 6
 
0.7%
2781 6
 
0.7%
2702 5
 
0.6%
2797 5
 
0.6%
2811 5
 
0.6%
Other values (122) 280
32.9%
(Missing) 509
59.9%
ValueCountFrequency (%)
2701 2
 
0.2%
2702 5
0.6%
2704 1
 
0.1%
2705 1
 
0.1%
2709 6
0.7%
2710 4
0.5%
2711 2
 
0.2%
2712 1
 
0.1%
2713 1
 
0.1%
2714 3
0.4%
ValueCountFrequency (%)
2880 1
 
0.1%
2879 2
 
0.2%
2874 1
 
0.1%
2873 5
0.6%
2872 4
0.5%
2871 2
 
0.2%
2870 1
 
0.1%
2869 1
 
0.1%
2867 3
0.4%
2866 1
 
0.1%
Distinct568
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-05-11T15:18:18.552536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length3.9376471
Min length1

Characters and Unicode

Total characters3347
Distinct characters280
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique434 ?
Unique (%)51.1%

Sample

1st row일신
2nd row백조
3rd row성심사
4th row동신사
5th row도래사
ValueCountFrequency (%)
백양 12
 
1.4%
현대 12
 
1.4%
백양사 11
 
1.3%
백조 9
 
1.0%
대우세탁소 9
 
1.0%
제일 9
 
1.0%
제일사 8
 
0.9%
현대사 7
 
0.8%
현대세탁 6
 
0.7%
현대세탁소 6
 
0.7%
Other values (569) 786
89.8%
2024-05-11T15:18:19.279312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
284
 
8.5%
273
 
8.2%
239
 
7.1%
166
 
5.0%
97
 
2.9%
90
 
2.7%
80
 
2.4%
66
 
2.0%
66
 
2.0%
56
 
1.7%
Other values (270) 1930
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3270
97.7%
Space Separator 25
 
0.7%
Decimal Number 19
 
0.6%
Uppercase Letter 13
 
0.4%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Lowercase Letter 6
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
284
 
8.7%
273
 
8.3%
239
 
7.3%
166
 
5.1%
97
 
3.0%
90
 
2.8%
80
 
2.4%
66
 
2.0%
66
 
2.0%
56
 
1.7%
Other values (247) 1853
56.7%
Uppercase Letter
ValueCountFrequency (%)
K 3
23.1%
S 3
23.1%
B 2
15.4%
G 1
 
7.7%
N 1
 
7.7%
L 1
 
7.7%
R 1
 
7.7%
M 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
w 1
16.7%
e 1
16.7%
d 1
16.7%
n 1
16.7%
a 1
16.7%
r 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
4 6
31.6%
8 4
21.1%
1 1
 
5.3%
6 1
 
5.3%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3270
97.7%
Common 58
 
1.7%
Latin 19
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
284
 
8.7%
273
 
8.3%
239
 
7.3%
166
 
5.1%
97
 
3.0%
90
 
2.8%
80
 
2.4%
66
 
2.0%
66
 
2.0%
56
 
1.7%
Other values (247) 1853
56.7%
Latin
ValueCountFrequency (%)
K 3
15.8%
S 3
15.8%
B 2
10.5%
G 1
 
5.3%
w 1
 
5.3%
e 1
 
5.3%
N 1
 
5.3%
d 1
 
5.3%
n 1
 
5.3%
a 1
 
5.3%
Other values (4) 4
21.1%
Common
ValueCountFrequency (%)
25
43.1%
2 7
 
12.1%
4 6
 
10.3%
( 6
 
10.3%
) 6
 
10.3%
8 4
 
6.9%
. 2
 
3.4%
1 1
 
1.7%
6 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3270
97.7%
ASCII 77
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
284
 
8.7%
273
 
8.3%
239
 
7.3%
166
 
5.1%
97
 
3.0%
90
 
2.8%
80
 
2.4%
66
 
2.0%
66
 
2.0%
56
 
1.7%
Other values (247) 1853
56.7%
ASCII
ValueCountFrequency (%)
25
32.5%
2 7
 
9.1%
4 6
 
7.8%
( 6
 
7.8%
) 6
 
7.8%
8 4
 
5.2%
K 3
 
3.9%
S 3
 
3.9%
B 2
 
2.6%
. 2
 
2.6%
Other values (13) 13
16.9%
Distinct469
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
Minimum1998-12-26 00:00:00
Maximum2024-05-03 12:04:15
2024-05-11T15:18:19.535490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:19.805107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
I
728 
U
122 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 728
85.6%
U 122
 
14.4%

Length

2024-05-11T15:18:20.061048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:20.274664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 728
85.6%
u 122
 
14.4%
Distinct114
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T15:18:20.527429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:20.794215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
일반세탁업
827 
빨래방업
 
12
운동화전문세탁업
 
8
세탁업 기타
 
3

Length

Max length8
Median length5
Mean length5.0176471
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반세탁업
2nd row일반세탁업
3rd row일반세탁업
4th row일반세탁업
5th row일반세탁업

Common Values

ValueCountFrequency (%)
일반세탁업 827
97.3%
빨래방업 12
 
1.4%
운동화전문세탁업 8
 
0.9%
세탁업 기타 3
 
0.4%

Length

2024-05-11T15:18:21.052074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:21.259043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 827
97.0%
빨래방업 12
 
1.4%
운동화전문세탁업 8
 
0.9%
세탁업 3
 
0.4%
기타 3
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct571
Distinct (%)77.2%
Missing110
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean202645.7
Minimum199578.09
Maximum205996.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-05-11T15:18:21.485569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199578.09
5-th percentile200457.86
Q1201327.42
median202454.51
Q3204036.11
95-th percentile205442.5
Maximum205996.72
Range6418.6307
Interquartile range (IQR)2708.6967

Descriptive statistics

Standard deviation1610.2216
Coefficient of variation (CV)0.0079459942
Kurtosis-1.0665605
Mean202645.7
Median Absolute Deviation (MAD)1300.9535
Skewness0.28875944
Sum1.4995782 × 108
Variance2592813.5
MonotonicityNot monotonic
2024-05-11T15:18:21.747904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200841.726990037 15
 
1.8%
200575.420521471 8
 
0.9%
203318.127254872 6
 
0.7%
201989.271689499 5
 
0.6%
202073.752578549 4
 
0.5%
201327.418241891 4
 
0.5%
203950.759833872 4
 
0.5%
203436.58838978 3
 
0.4%
201704.707876218 3
 
0.4%
201517.385329678 3
 
0.4%
Other values (561) 685
80.6%
(Missing) 110
 
12.9%
ValueCountFrequency (%)
199578.087266761 1
0.1%
199668.574769372 1
0.1%
199764.396533537 1
0.1%
199841.912708041 1
0.1%
199867.984001337 1
0.1%
199870.752714322 1
0.1%
199872.097127135 1
0.1%
199887.379548552 1
0.1%
199888.694291511 1
0.1%
199901.384837193 2
0.2%
ValueCountFrequency (%)
205996.717928956 3
0.4%
205818.852385165 2
0.2%
205733.885475417 3
0.4%
205728.527460287 1
 
0.1%
205669.363368797 1
 
0.1%
205667.647299339 1
 
0.1%
205663.651941359 1
 
0.1%
205653.540123724 1
 
0.1%
205652.772334765 1
 
0.1%
205651.803155309 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct571
Distinct (%)77.2%
Missing110
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean455676.72
Minimum452958.92
Maximum457803.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-05-11T15:18:21.986423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452958.92
5-th percentile453625.82
Q1454811.06
median455944.16
Q3456566.6
95-th percentile457245.71
Maximum457803.26
Range4844.3478
Interquartile range (IQR)1755.5423

Descriptive statistics

Standard deviation1126.2612
Coefficient of variation (CV)0.0024716233
Kurtosis-0.7109188
Mean455676.72
Median Absolute Deviation (MAD)786.69329
Skewness-0.47618022
Sum3.3720077 × 108
Variance1268464.3
MonotonicityNot monotonic
2024-05-11T15:18:22.693605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454721.505180141 15
 
1.8%
457360.617372111 8
 
0.9%
456078.982123486 6
 
0.7%
455190.095862939 5
 
0.6%
456449.07069121 4
 
0.5%
455410.800040067 4
 
0.5%
456827.893211245 4
 
0.5%
455242.326727458 3
 
0.4%
455171.670762264 3
 
0.4%
456504.561867278 3
 
0.4%
Other values (561) 685
80.6%
(Missing) 110
 
12.9%
ValueCountFrequency (%)
452958.916836799 1
0.1%
453036.744985063 1
0.1%
453060.946220955 1
0.1%
453090.883859781 1
0.1%
453097.336374 1
0.1%
453102.822525082 1
0.1%
453113.800128438 1
0.1%
453141.559698754 1
0.1%
453201.399559715 1
0.1%
453213.188602211 1
0.1%
ValueCountFrequency (%)
457803.264646008 1
0.1%
457678.401608072 1
0.1%
457667.199817772 1
0.1%
457664.624149181 2
0.2%
457581.254031821 2
0.2%
457542.951622306 1
0.1%
457520.02297058 1
0.1%
457454.696567455 1
0.1%
457424.456073026 1
0.1%
457420.995102733 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
일반세탁업
778 
<NA>
 
56
빨래방업
 
11
운동화전문세탁업
 
4
세탁업 기타
 
1

Length

Max length8
Median length5
Mean length4.9364706
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row일반세탁업
2nd row일반세탁업
3rd row일반세탁업
4th row일반세탁업
5th row일반세탁업

Common Values

ValueCountFrequency (%)
일반세탁업 778
91.5%
<NA> 56
 
6.6%
빨래방업 11
 
1.3%
운동화전문세탁업 4
 
0.5%
세탁업 기타 1
 
0.1%

Length

2024-05-11T15:18:22.992947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:23.284497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 778
91.4%
na 56
 
6.6%
빨래방업 11
 
1.3%
운동화전문세탁업 4
 
0.5%
세탁업 1
 
0.1%
기타 1
 
0.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.3%
Missing174
Missing (%)20.5%
Infinite0
Infinite (%)0.0%
Mean1.4349112
Minimum0
Maximum15
Zeros301
Zeros (%)35.4%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-05-11T15:18:23.474231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6493034
Coefficient of variation (CV)1.1494114
Kurtosis6.2321866
Mean1.4349112
Median Absolute Deviation (MAD)1
Skewness1.5051809
Sum970
Variance2.7202016
MonotonicityNot monotonic
2024-05-11T15:18:23.683328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 301
35.4%
3 131
15.4%
1 89
 
10.5%
2 87
 
10.2%
4 49
 
5.8%
5 10
 
1.2%
7 5
 
0.6%
6 3
 
0.4%
15 1
 
0.1%
(Missing) 174
20.5%
ValueCountFrequency (%)
0 301
35.4%
1 89
 
10.5%
2 87
 
10.2%
3 131
15.4%
4 49
 
5.8%
5 10
 
1.2%
6 3
 
0.4%
7 5
 
0.6%
15 1
 
0.1%
ValueCountFrequency (%)
15 1
 
0.1%
7 5
 
0.6%
6 3
 
0.4%
5 10
 
1.2%
4 49
 
5.8%
3 131
15.4%
2 87
 
10.2%
1 89
 
10.5%
0 301
35.4%
Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
422 
0
378 
1
44 
2
 
5
4
 
1

Length

Max length4
Median length1
Mean length2.4894118
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 422
49.6%
0 378
44.5%
1 44
 
5.2%
2 5
 
0.6%
4 1
 
0.1%

Length

2024-05-11T15:18:24.001393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:24.291034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 422
49.6%
0 378
44.5%
1 44
 
5.2%
2 5
 
0.6%
4 1
 
0.1%
Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
1
349 
0
250 
<NA>
200 
2
43 
3
 
7

Length

Max length4
Median length1
Mean length1.7058824
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 349
41.1%
0 250
29.4%
<NA> 200
23.5%
2 43
 
5.1%
3 7
 
0.8%
6 1
 
0.1%

Length

2024-05-11T15:18:24.534475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:24.802418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 349
41.1%
0 250
29.4%
na 200
23.5%
2 43
 
5.1%
3 7
 
0.8%
6 1
 
0.1%

사용끝지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)1.5%
Missing447
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean1.8387097
Minimum0
Maximum302
Zeros23
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-05-11T15:18:25.009693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum302
Range302
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.998384
Coefficient of variation (CV)8.157016
Kurtosis402.01649
Mean1.8387097
Median Absolute Deviation (MAD)0
Skewness20.038311
Sum741
Variance224.95153
MonotonicityNot monotonic
2024-05-11T15:18:25.222362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 328
38.6%
2 45
 
5.3%
0 23
 
2.7%
3 5
 
0.6%
6 1
 
0.1%
302 1
 
0.1%
(Missing) 447
52.6%
ValueCountFrequency (%)
0 23
 
2.7%
1 328
38.6%
2 45
 
5.3%
3 5
 
0.6%
6 1
 
0.1%
302 1
 
0.1%
ValueCountFrequency (%)
302 1
 
0.1%
6 1
 
0.1%
3 5
 
0.6%
2 45
 
5.3%
1 328
38.6%
0 23
 
2.7%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
515 
0
326 
1
 
9

Length

Max length4
Median length4
Mean length2.8176471
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 515
60.6%
0 326
38.4%
1 9
 
1.1%

Length

2024-05-11T15:18:25.461350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:25.657693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 515
60.6%
0 326
38.4%
1 9
 
1.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
748 
0
95 
1
 
7

Length

Max length4
Median length4
Mean length3.64
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 748
88.0%
0 95
 
11.2%
1 7
 
0.8%

Length

2024-05-11T15:18:25.853281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:26.039350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 748
88.0%
0 95
 
11.2%
1 7
 
0.8%

한실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
449 
0
401 

Length

Max length4
Median length4
Mean length2.5847059
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 449
52.8%
0 401
47.2%

Length

2024-05-11T15:18:26.257827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:26.465168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 449
52.8%
0 401
47.2%

양실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
449 
0
401 

Length

Max length4
Median length4
Mean length2.5847059
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 449
52.8%
0 401
47.2%

Length

2024-05-11T15:18:26.665451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:26.886363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 449
52.8%
0 401
47.2%

욕실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
449 
0
401 

Length

Max length4
Median length4
Mean length2.5847059
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 449
52.8%
0 401
47.2%

Length

2024-05-11T15:18:27.109600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:27.356827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 449
52.8%
0 401
47.2%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing60
Missing (%)7.1%
Memory size1.8 KiB
False
790 
(Missing)
 
60
ValueCountFrequency (%)
False 790
92.9%
(Missing) 60
 
7.1%
2024-05-11T15:18:27.543938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
449 
0
401 

Length

Max length4
Median length4
Mean length2.5847059
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 449
52.8%
0 401
47.2%

Length

2024-05-11T15:18:27.748001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:27.947535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 449
52.8%
0 401
47.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing850
Missing (%)100.0%
Memory size7.6 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
801 
임대
 
47
자가
 
2

Length

Max length4
Median length4
Mean length3.8847059
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 801
94.2%
임대 47
 
5.5%
자가 2
 
0.2%

Length

2024-05-11T15:18:28.150502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:28.369126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 801
94.2%
임대 47
 
5.5%
자가 2
 
0.2%

세탁기수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
667 
0
 
66
1
 
48
2
 
45
3
 
17

Length

Max length4
Median length4
Mean length3.3541176
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 667
78.5%
0 66
 
7.8%
1 48
 
5.6%
2 45
 
5.3%
3 17
 
2.0%
4 7
 
0.8%

Length

2024-05-11T15:18:28.595458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:28.825949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 667
78.5%
0 66
 
7.8%
1 48
 
5.6%
2 45
 
5.3%
3 17
 
2.0%
4 7
 
0.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
818 
0
 
32

Length

Max length4
Median length4
Mean length3.8870588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 818
96.2%
0 32
 
3.8%

Length

2024-05-11T15:18:29.054068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:29.276647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 818
96.2%
0 32
 
3.8%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
818 
0
 
32

Length

Max length4
Median length4
Mean length3.8870588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 818
96.2%
0 32
 
3.8%

Length

2024-05-11T15:18:29.451795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:29.667365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 818
96.2%
0 32
 
3.8%

회수건조수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.8%
Missing691
Missing (%)81.3%
Infinite0
Infinite (%)0.0%
Mean0.97484277
Minimum0
Maximum6
Zeros30
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-05-11T15:18:29.866341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78715708
Coefficient of variation (CV)0.80747081
Kurtosis13.35493
Mean0.97484277
Median Absolute Deviation (MAD)0
Skewness2.7255014
Sum155
Variance0.61961627
MonotonicityNot monotonic
2024-05-11T15:18:30.083783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 115
 
13.5%
0 30
 
3.5%
2 8
 
0.9%
4 3
 
0.4%
3 2
 
0.2%
6 1
 
0.1%
(Missing) 691
81.3%
ValueCountFrequency (%)
0 30
 
3.5%
1 115
13.5%
2 8
 
0.9%
3 2
 
0.2%
4 3
 
0.4%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
4 3
 
0.4%
3 2
 
0.2%
2 8
 
0.9%
1 115
13.5%
0 30
 
3.5%

침대수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
<NA>
693 
0
157 

Length

Max length4
Median length4
Mean length3.4458824
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 693
81.5%
0 157
 
18.5%

Length

2024-05-11T15:18:30.350351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:30.582832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 693
81.5%
0 157
 
18.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing56
Missing (%)6.6%
Memory size1.8 KiB
False
794 
(Missing)
 
56
ValueCountFrequency (%)
False 794
93.4%
(Missing) 56
 
6.6%
2024-05-11T15:18:30.752189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030700003070000-205-1987-0230619870724<NA>3폐업2폐업20021202<NA><NA><NA>020926802527.60136055서울특별시 성북구 동선동5가 17-0번지<NA><NA>일신2003-06-03 00:00:00I2018-08-31 23:59:59.0일반세탁업201365.230237454794.43719일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130700003070000-205-1987-0230819870617<NA>3폐업2폐업20021202<NA><NA><NA>020916407310.18136865서울특별시 성북구 하월곡동 59-12번지<NA><NA>백조2003-06-03 00:00:00I2018-08-31 23:59:59.0일반세탁업203280.52397455896.59659일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230700003070000-205-1987-0231019871215<NA>3폐업2폐업20021202<NA><NA><NA>020926392332.46136053서울특별시 성북구 동선동3가 259-7번지<NA><NA>성심사2003-06-03 00:00:00I2018-08-31 23:59:59.0일반세탁업201855.856552454915.901292일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330700003070000-205-1987-0231219870722<NA>3폐업2폐업20080421<NA><NA><NA>020926397356.00136054서울특별시 성북구 동선동4가 90-1번지<NA><NA>동신사2003-03-13 00:00:00I2018-08-31 23:59:59.0일반세탁업201457.850372454593.354918일반세탁업4<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430700003070000-205-1987-0231319870711<NA>1영업/정상1영업<NA><NA><NA><NA>020924103026.40136052서울특별시 성북구 동선동2가 142-0번지서울특별시 성북구 보문로30길 72 (동선동2가)2844도래사2015-12-31 10:05:42I2018-08-31 23:59:59.0일반세탁업201696.155434454267.219208일반세탁업101100000N0<NA><NA><NA><NA>0<NA><NA>10N
530700003070000-205-1987-0231519870617<NA>3폐업2폐업20060711<NA><NA><NA>02 914412623.10136873서울특별시 성북구 하월곡동 88-450번지<NA><NA>원흥사2003-03-17 00:00:00I2018-08-31 23:59:59.0일반세탁업202620.050097455888.837484일반세탁업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630700003070000-205-1987-0231719870619<NA>3폐업2폐업19950328<NA><NA><NA>02 915482915.12136858서울특별시 성북구 종암동 4-5번지<NA><NA>백양사2001-09-27 00:00:00I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730700003070000-205-1987-0232019870619<NA>3폐업2폐업19960415<NA><NA><NA>02 912189919.18136864서울특별시 성북구 종암동 3-260번지<NA><NA>제일2001-09-27 00:00:00I2018-08-31 23:59:59.0일반세탁업203072.714962455272.98731일반세탁업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830700003070000-205-1987-0232119870709<NA>3폐업2폐업20021202<NA><NA><NA>020763869039.60136821서울특별시 성북구 성북동 63-44번지<NA><NA>제일2003-06-03 00:00:00I2018-08-31 23:59:59.0일반세탁업199901.384837454568.271866일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930700003070000-205-1987-0232319870526<NA>3폐업2폐업20091130<NA><NA><NA>020923411123.10136044서울특별시 성북구 삼선동4가 340-0번지<NA><NA>일광2003-03-06 00:00:00I2018-08-31 23:59:59.0일반세탁업201205.871624454206.035334일반세탁업3<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
84030700003070000-205-2020-000032020-08-19<NA>3폐업2폐업2023-12-26<NA><NA><NA><NA>26.40136-820서울특별시 성북구 석관동 338-156서울특별시 성북구 화랑로30길 26 (석관동)2790삼성세탁2023-12-26 13:20:00U2022-11-01 22:08:00.0일반세탁업204867.543707456362.191782<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84130700003070000-205-2020-0000420201214<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.05136848서울특별시 성북구 정릉동 239 정릉풍림아이원서울특별시 성북구 솔샘로25길 20, 정릉풍림아이원 상가1동 103호 (정릉동)2702풍림아이원세탁소2020-12-14 10:23:43I2020-12-16 00:23:06.0일반세탁업200575.420521457360.617372일반세탁업10<NA><NA><NA><NA>000N0<NA><NA><NA><NA>20020N
84230700003070000-205-2021-0000120210820<NA>1영업/정상1영업<NA><NA><NA><NA><NA>74.09136825서울특별시 성북구 성북동 173-23서울특별시 성북구 성북로10가길 4, 1층 (성북동)2835순수세탁2021-08-20 16:33:10I2021-08-24 00:22:50.0일반세탁업200223.39218454416.817156일반세탁업000000000N0<NA><NA><NA><NA>00000N
84330700003070000-205-2022-0000120220307<NA>3폐업2폐업20220411<NA><NA><NA><NA>39.60136817서울특별시 성북구 석관동 182-27서울특별시 성북구 한천로80길 3, 1층 (석관동)2781태양세탁2022-04-11 11:13:07U2021-12-03 23:03:00.0일반세탁업205456.466415456567.134053<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84430700003070000-205-2022-0000220220411<NA>3폐업2폐업20220622<NA><NA><NA><NA>39.60136817서울특별시 성북구 석관동 182-27서울특별시 성북구 한천로80길 3, 1층 (석관동)2781세탁나라2022-06-22 13:55:04U2021-12-05 22:04:00.0일반세탁업205456.466415456567.134053<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84530700003070000-205-2022-0000320220823<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.00136130서울특별시 성북구 하월곡동 225-6 래미안월곡아파트서울특별시 성북구 오패산로 84, 래미안월곡아파트 203호 (하월곡동)2741삼성래미안 세탁2022-08-23 13:51:00I2021-12-07 22:05:00.0일반세탁업203112.240099456365.663667<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84630700003070000-205-2023-000012023-06-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.00136-890서울특별시 성북구 돈암동 42-32 고명아파트서울특별시 성북구 북악산로 865, 1층 점포1호 (돈암동, 고명아파트)2817슈즈크린2023-06-13 13:34:17I2022-12-05 23:05:00.0운동화전문세탁업201704.707876455171.670762<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84730700003070000-205-2023-000022023-07-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>43.20136-042서울특별시 성북구 삼선동2가 107-2서울특별시 성북구 삼선교로14길 14-5, 1층 (삼선동2가)2864신라세탁2023-07-28 13:26:49I2022-12-06 21:00:00.0일반세탁업200815.780283453901.321558<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84830700003070000-205-2024-000012024-01-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00136-837서울특별시 성북구 장위동 233-251서울특별시 성북구 장위로 80, 1층 (장위동)2745덕영사2024-01-24 09:42:01I2023-11-30 22:06:00.0일반세탁업203950.759834456827.893211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84930700003070000-205-2024-000022024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>105.00136-045서울특별시 성북구 삼선동5가 14서울특별시 성북구 삼선교로18길 59, 1층 (삼선동5가)2862그린세탁2024-05-03 12:04:15I2023-12-05 00:05:00.0일반세탁업201256.764043454124.59806<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>